Abstract Today, early disease detection (EDD) is a matter of more importance than ever in medicine. Upon interaction with human plasma, nanoparticles are covered by proteins leading to formation of a biomolecular corona (BC). As the protein patterns of patients with conditions differ from those of healthy subjects, current research into technologies based on the exploitation of personalized BC patterns could be a turning point for early disease detection. Here, we present a framework based on principal component analysis of large personalized BC datasets. We comment on how principal component analysis of personalized BC data is a fundamental step towards turning the output of basic research into fast, safe and inexpensive technologies with superior prediction ability than current methods.

中文翻译：

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用于早期疾病检测的个性化生物分子电晕数据的主成分分析

摘要 如今，早期疾病检测 (EDD) 在医学中比以往任何时候都更加重要。与人体血浆相互作用后，纳米粒子被蛋白质覆盖，导致形成生物分子电晕 (BC)。由于疾病患者的蛋白质模式与健康受试者的蛋白质模式不同，当前基于开发个性化 BC 模式的技术研究可能成为早期疾病检测的转折点。在这里，我们提出了一个基于大型个性化 BC 数据集的主成分分析的框架。我们评论了个性化 BC 数据的主成分分析如何是将基础研究的成果转化为具有比当前方法更优越的预测能力的快速、安全和廉价技术的基本步骤。